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Image Analysis, Random Fields and Dynamic Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability #27) book cover by Gerhard Winkler
Paperback

Image Analysis, Random Fields and Dynamic Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability #27)

by Gerhard Winkler

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Paperback · 324 pages Springer Berlin Heidelberg · 2012

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About the book

Image Analysis, Random Fields and Dynamic Monte Carlo Methods

This text is concerned with a probabilistic approach to image analysis as initiated by U. GRENANDER, D. and S. GEMAN, B.R. HUNT and many others, and developed and popularized by D. and S. GEMAN in a paper from 1984. It formally adopts the Bayesian paradigm and therefore is referred to as 'Bayesian Image Analysis'. There has been considerable and still growing interest in prior models and, in particular, in discrete Markov random field methods. Whereas image analysis is replete with ad hoc techniques, Bayesian image analysis provides a general framework encompassing various problems from imaging. Among those are such 'classical' applications like restoration, edge detection, texture discrimination, motion analysis and tomographic reconstruction. The subject is rapidly developing and in the near future is likely to deal with high-level applications like object recognition. Fascinating experiments by Y. CHOW, U. GRENANDER and D.M. KEENAN (1987), (1990) strongly support this belief.

Details

Publisher
Springer Berlin Heidelberg
Author
Gerhard Winkler
Format
Paperback
Published
Jan 19, 2012
ISBN-13
9783642975240
Pages
324
Printing
Printed on demand
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